Our Thinking

Freeing Business Users to be Part of the Story

Welcome to the Moneyball economy. With a fraction of a point separating competitors in this economy, the next strategic bet companies need to make to stay ahead of the competition is investing in applications that enable data driven decisions.  Using business analytics as a competitive advantage is a modern problem. And modern problems require modern solutions.

The last mile of analytics is broken – and we’re fooled by the noise
Think about it. You can ask a large number of your colleagues at work to start a fantasy football pool, create a plan and forecast who’s going to win in matter of minutes – reports, stats, and graphics with embedded collaboration so everyone can actively participate and affect the outcome. Where is the analytics equivalent in the enterprise? In general, we are mired in spreadsheets and antiquated tools for financial and operational planning and analytics. We have enormous books of reports that hardly anyone reads, dashboards that only a few people understand, and all of it is out of context. This results in incredible frustration for business users. They’ve been conditioned by their consumer experiences: simple, elegant and actionable interfaces, and they are demanding more from their enterprise experience. Without the engagement of these users, it will be impossible to align strategy with execution in the Moneyball economy.

And then there is the challenge of dealing with increased amounts of data and an overhyped Big Data industry. The few people with the power to provide analysis to the organization often fall prey to the tendency to cherry-pick what they think matters most and provide a subset of the data that fits what they want to believe. The larger the data set becomes, the harder it is to tell the correct story – we are fooled by the noise more than ever.

Frustration, not necessity, is the mother of invention
When we started Tidemark three years ago, we set out to re-imagine business analytics. At the core, my belief, shaped by years of seeking freedom growing up in a communist country, is that analytic applications that give companies a way to better understand their business and empower more people within an organization to make intelligent business decisions is a wonderful way forward for the enterprise analytics space. Over the last year we have introduced financial and operational analytic applications that are helping companies gain visibility, transparency and competitive advantage that is unprecedented.

Having put in place the fundamentals (analytical processes, a user experience designed for the business user, in-context collaboration, analysis, assumptions, and modeling that is mobile first) we turned our attention to the last mile – how to tell the story of what’s happening.

Born from the frustration of the antiquated and fatigued offerings for business reporting and dashboarding, we wanted to innovate and re-imagine what business reporting should look like in the 21st century. Freeing business users from tools designed for the era of green-bar reports and static, out of context dashboards and visualizations became our guiding light, and the cornerstone for our latest release of applications.

We wanted a new way to help companies create, tell and share their stories with the world. This democratization of information drives actionability and ultimately helps companies transform themselves to better compete, growing revenue and profit.

What’s the story anyway?
Storyline samplesToday, as part of our spring ’13 release, we are introducing Tidemark Storylines™  – an innovative way for organizations to create, share and impact their performance in the context of financial and operational processes. Storylines provide a way for everyone in the organization to tell the story and actively participate  in driving the performance of the company forward.

Tidemark Storylines are actionable visualizations that are dynamically generated – weaving together internal data, segmentation (products, regions, customers), unstructured contextual data (assumptions, comments, annotations) and large streams correlation (Twitter™, Bloomberg™, RFID data). This combination is used to create the contextual narrative of what’s happening in your business and what you can do about it.

These data visualizations tell the real story of vital business processes - Overall Company Health, What Happens If, Forecast Variances, Profitability, and People – and are grounded in real-time data that lets users instantly understand the impact of taking action.

Storylines combine visualizations with actions – the data set is composed on-demand based on what the business users need and how they want to participate. .

Even more exciting, Tidemark Storylines™ can be easily shared across the entire organization, bringing freedom of access and action to people that have never before been served by analytics providers.

As an example, telling the story of profitability provides:

  • Real-time analysis of company performance and the customers, regions, products and channels that are making the greatest impact
  • Dynamic control of how specific actions impact overall profitability with a visual depiction of what happens and why

Profitability storyline excerpt

And since most of the data that matters in today’s volatile market exists outside the walls of the enterprise, we also bring in external data and correlate it into the context of the story. Some examples include:

 

  • Correlation of external insights (weather reports, financial market insight, social conversations, etc.) with internal information for a holistic view of the data
  • Integration of assumptions, annotations and conversations to enrich the context of what’s happening and why

 

  • Tidemark Actions that allow users to go directly into the analytical process that was used to create the story and share the impact of their changes;

Process Metrics excerpt

Here’s the entire Storyline and the Tidemark analytical process that generated it:

Tidemark Storylines further our mission to democratize business analytics by providing actionability to make intelligent decisions.

I am very excited and humbled to share the story that shaped Tidemark Storylines, and I am extremely grateful to our customers, our close partners, my amazing team and the support of our board in bring it to life.

To learn more, go to http://www.tidemark.net/storylines or follow @TidemarkEPM or me on Twitter @optian.

 

THE KARAOKE EFFECT

When I started Tidemark, I began with a marvelous vision for the company. In my mind, the story’s intricate and powerful details fit together like a Beethoven symphony, but when I told the story to investors I sounded like a tone-deaf drunk in a karaoke bar.  What the hell happened?

It turns out that coming up with the story is entirely different than articulating the story. In fact, articulating the story can be more time consuming and difficult than inventing it in the first place.

Despite being incredibly hard, as a founder there is perhaps nothing more important than being able to convey the story arc of your vision, of what you are after and why it matters. Pitch perfect.

Often we have to do so with a large array and diverse audience. Why should customers care about what you are offering? Are you a “must-have” or a nicer way to do something that’s already done? How are you different? Why are you after this?

Giancarlo

Armiliato as Giancarlo in To Rome with Love

*In Woody Allen’s excellent To Rome with Love, Giancarlo a proud father who’s day job is that of a mortician, sings in the shower and Jerry, a retired—and critically reviled—opera director played by Allen himself, feels inspired to bring Giancarlo’s gift to the public. Jerry convinces a reluctant Giancarlo to audition in front of a room of opera bigwigs, but Giancarlo performs poorly in this setting.

What Jerry realizes is that Giancarlo’s talent is tied to the comfort and freedom he feels in the shower and in a particularly funny and smart series of scenes, Jerry and Giancarlo decide to stage the opera Pagliacci, with an incongruous shower present in all scenes. Giancarlo receives rave reviews. We are all, of course, perfect singing in the car by ourselves.

Short of bringing the shower with us every time we talk about what we are building, what are some of the things that can help remove the karaoke effect?

Here are some things that I found helpful:

  • Embrace solitude and precision. In a recent New York Times interview, Jerry Seinfeld talks about his creative process seeking perfection. He will nurse a single joke for years, amending, abridging and reworking it incrementally, to get the thing just so.
  • Freedom to pursue the improbable removes the uncomfortable feeling that nobody gets your story. As Aaron Levie the CEO and Co-Founder of Box passionately talks about in Be on a mission that doesn’t suck working on something that is ambitious, improbable, and fundamentally thrilling will keep you cranking day after day, constantly refining and seeking what matters.
  • Be quotable. Strive for a clear, concise and quotable foundational story as the glue that holds and inspires the management team, the various teams inside the company and your early customers.
  • Practice makes perfect.  There is no other way around the “10,000 hour rule” that Malcolm Gladwell introduced with his book, Outliers.

Telling your story isn’t just about marketing. It’s about leadership. Great people will only want to pursue great visions. If you can’t articulate your potential greatness, you will never hire and motivate the kind of people who will make it happen.

Anyone up for a rendition of “Dream On” by Aerosmith?

Christian Gheorghe is the Founder and CEO of Tidemark.net a cloud-based enterprise analytics company re-imaging business analytics for business people. He can be reached at cgheorghe@tidemark.net or @optian on twitter.

*The synopsis for To Rome with Love is from Wikipedia lightly edited for readability.

Beyond Big Data Hype – Looking for productivity

 

“In God we trust, all others must bring data.”

                                                – W. Edwards Deming

 

How do you use data today to improve the performance of your business?  I often ask this question when I speak to business leaders, customers and prospects to understand how they think about data.   Having been in the analytics space for twenty years, I have never seen more interest in analytics than I am seeing now.   With the arrival of cloud technologies and new innovations, turning data into improved productivity and better business results is high on the executive agenda.

 

No doubt this increased interest and awareness in the power of data is due in part to all the market excitement around Big Data.  Regardless of industry or market segment, companies of all types and sizes are now adding big data to the list of business and IT priorities, often with little or no idea what big data is.  Interestingly, business owners often have little idea what data is available to them today and they struggle to even articulate a strategy or to point to examples where data is helping them deliverable measureable return.  While the data may be big, the business results to date have not been.

 

Mike Healey of Yeoman Technology Group just authored InformationWeek’s just published new research report titled, “The Six Lies of Big Data,” providing yet more color and some interesting statistics to the market trend and hype about big data.  The survey of more than 250 business technology professionals provides a number of interesting nuggets which suggest both missed opportunities, and the promise of better productivity and performance.

 

Interestingly, when the survey asked about the organizational approach to data, 61% of respondents indicated that their organizations were either leading users or best in class and heavily guided by data to manage across the organization.

 

This type of response would suggest that data access and analytic applications are now pervasive, enabling everyone in the business to do complex analysis, build scenarios and plans, and deliver real business value.  Has the era of easy access to information to optimize and take action to improve performance finally arrived?

 

Not so fast

 

A review of the survey responses starts to reveal a different picture.  Similar to discussions my team has with prospects and customers, there is high interest in capturing and using data, but most companies are still stuck  with legacy tools, disconnected solutions and no connection between operational plans and business reality.  Enterprise solutions, business owner access, and IT readiness is not there yet.

 

The first big reality check for many companies is in the solutions they make available to the business.  Often these are point solutions or dashboards, supported by analysts behind the scenes with highly customized tools and spreadsheets.  This is reflected in the IW survey.  Excel as a big data tool is not an enterprise strategy.

When you dig into some of the additional details of the survey, the picture gets even worse.

  • Only a third of companies plan to spend more on training and development around data analysis
  • 17% are growing staffing around analytics, while 14% are cutting back
  • 65% of companies are using Excel, with 20% of all analysis happening via Excel spreadsheets

 

 

Most organizations aspire to making analytics – capturing and making data that helps people optimize and act to improve performance – a core competency if not an area of strength in their organizations, but there are few companies where this is true today.  Even with highly sophisticated teams, analysts across departments and even data scientists, it is the rare company that can connect data and people to deliver advantage.

 

Big Data vs. Small Data

 

Most organizations struggle to get meaningful, sustained value out of their small data sources, much less tackling “big data.”  This includes basics like CRM data, HCM and ERP data, much less web and social data. And to the degree they do capture and extract the information, the leading technical approaches include Microsoft SQL and information discovery tools and the latest appliance from Oracle.  None of these solutions are particularly business user friendly, and can’t bring all the data together in a way that makes it easy for business people to do analysis, much less find the trend, manage risk, or proactively manage.

 

Tellingly, when respondents were asked for the biggest barriers to successfully using Big Data in the organization, the number one barrier to success was budget.

 

 

With almost 40% of respondents claiming financial hardship, the data seems to suggest that Big Data is perceived as yet another IT project and added cost vs. competitive advantage for the organization.  It is safe to say that all the vendor and tech press excitement about big data has yet to materialize in business cases that show repeatable and measureable business productivity and impact.

 

Big data is meaningless unless it is connecting to meaningful business value – faster inventory turns, cost take out, increased sales velocity, improved customer satisfaction.   Data and other projects that can’t directly improve the way people do their jobs is of low utility for most organizations.

 

The hidden gem in the report is the reference to Erik Brynjolfsson’s MIT research on publically traded companies that focused their decision making on data analysis.  Of the 179 public companies he surveyed, Brynjolfsson concluded that companies using data-driven approaches to decisions had 5% to 6% greater productivity than their peers.  In short, a culture of data driven decision-making consistently applied produces superior results.

 

When you apply 5% improved productivity to a large organization with tens of thousands of employees, the impact can be substantial, especially when compounded year over year.  Making data and analytics available for all users across the departments and functional areas delivers meaningful return.  When we talk about re-imaging business analytics for everyone in the business to change the way they work, this is exactly the type of performance gain we believe companies should expect.

 

The discussion and hand waving around Big Data could be just a passing trend. What is not, is the need to turn any and all data into context and action for the business user.
Time to bring the data – big productivity awaits.

 

Five for Friday with George Jaquette

Today’s five for friday interview is a discussion with our new VP of Engineering, George Jaquette.  George shares his insights on cloud, innovation, mentoring and leadership.  We are thrilled to have George on our team.  Please meet George Jaquette.

PM:  You just joined Tidemark as our VP of Engineering.  Tell us a little about your background and what attracted you to Tidemark.

George Jaquette, VP Engineering at Tidemark

GJ:  I am an engineer at heart and have been building things since I was a kid. I love to solve problems and have a streak of MacGyver in me. The past five years have given me some real perspective about the interesting opportunities to change the way businesses run with SaaS solutions, and Tidemark embodies some of the key levers that developers can move — mobile applications first, empowering employees with information throughout the organization, and building new solutions unconstrained by legacy products. The team, the technology and the opportunity for Tidemark are all part of what makes this role perfect for me.

PM:  How has the cloud changed software development?
GJ:  The time and distance from a developers keyboard to a delighted user is greatly reduced through cloud delivery. Having worked in a world where release cycles were measured in years, and where a box of parts was sold as an answer “custom built for the end user by an army of consultants”, we have moved to a world where everyone is on the same great release, where issues are addressed for everyone at the same time, and where new features and capabilities can be delivered without an expensive and painful migration. There is of course a sharp side to this knife too — any problems created by a cloud vendor impact all customers immediately, and shared resources have to be managed and shared well. The short distance from keyboard to user raises the bar for quality and uptime, which really creates a win-win situation where engineers are motivated to deliver higher quality and benefit from much quicker feedback.
PM:  How do you think about innovation?
GJ:  Innovation is a challenge for most successful businesses because it is hard to schedule innovation and it is hard to screen for it when you are hiring. Innovation in my opinion is the ability to see through and around obstacles, the ability to see a solution instead of the problems between you and that solution. One of my favorite movie scenes is outside the castle walls in Princess Bride, when our paralyzed hero says “Now why didn’t you mention that we had a wheelbarrow?!” When you have limited resources, big challenges, and motivated competition your best way forward is to out-innovate, out-think, and out-deliver. Big companies try to schedule white space time and try to encourage innovative processes, but in my experience real innovation happens at small companies tackling big challenges in new and different ways accepting the risk of absolute failure. Innovators have their bad days too, and the mindset of trying again in a different way rather than retreating to the old proven method is what defines innovation.
PM:  You are hiring for engineering and development roles – beyond technical skills, what is the profile of your ideal candidate?
GJ:  We are looking for smart people who can contribute more than code, and we value creativity and curiosity over experience. We want team players who question assumptions, who take ownership for and pride in their work, and who have shown a lifelong desire to learn. When we are reading resumes, we want to be impressed by the candidate’s measurable contributions — what did they do that really mattered to their group, their company, their customers. Certifications and courses matter less than a track record of delivering powerful applications or innovative solutions. We work very closely with every group in the company, so we very much want flexible and friendly people here at Tidemark.
PM:  Who do you consider your mentors and what did you learn from them?
GJ:  I have to admit that I haven’t read the biographies or autobiographies of famous business leaders like Jack Welch or Steve Jobs. My respect is much more local — for the people who invested time in me and who took the time to connect with me on a personal level. I learned from Terry Algeo, my first boss, that it is important to spend time ensuring that everyone knows what to do and that everyone feels connected to the team’s objectives (he owns and manages a chain of laundries). The coaches who taught me soccer and water polo (Mr. Noble and Mr. Metz respectively) as a youth made a huge impact on my life and they showed me what it means to be a team leader, something not every VP ever learns. From my perspective, mentoring is an informal process of teaching by doing and leading by example, and the mentors I most respect are the ones that treat everyone with respect, assume good intentions and great potential in each person, and spend the time to learn each individual’s strengths and weaknesses.
An unusual observation to share is that sometimes the hardest lessons to learn are those that must be learned in the negative — like the “Aha!” moment when a positional leader declares how proud he is that he is an a**hole, and you realize that he is serious. Some of the most powerful influences on my own style come from leaders in the negative sense, who for obvious reasons I won’t identify by name.
So, how has this shaped me and my leadership style? I am committed to treating every person with respect, whether it is returned or not. I am committed to telling the truth, and to giving as much insight as I can reasonably share when people are confused or hurt. I believe that managing is like coaching. I have coached adults, teenagers, and children and the insights are the same — set clear expectations, give immediate feedback, deliver nine times as much positive affirmation as negative feedback, and whenever possible spell out clear role definition so each team member knows how his or her efforts contribute to the team’s success. Take the time to celebrate victories, and learn to accept defeat but always learn from it. Make it fun, and make sure that your score reflects the game you want to play — keep the right score.

 

Data scientists and the future of work

Recently there has been a fair amount of discussion about the need for data scientists in a big data world.  The base argument being that as access and ubiquity of data has exploded, so has the need for experts to absorb and interpret the data and put it to good use.   This article of faith seems to be widely accepted and a recent study by McKinsey suggests lack of data scientists as a potential limitation to innovation and business growth.
This discussion took an interesting turn several weeks ago with Gil Press’s intriguing blog in Forbes suggesting that data scientists will actually be replaced by tools.  This is a topic suggestion for SXSW and it also generated some interesting responses in the comments section of the blog as it opens the question of whether this is yet another area where machine learning will catch up and ultimately replace humans.

While the topic is interesting, the premise that data tools somehow replace humans is flawed.  Our cars and automotive diagnostic equipment have gotten both much smarter and automated, but when your car breaks down or alerts you that it is time for a tune up, you still take it to a mechanic.   A better question would be, how long will be before everyone is a “data scientist”?

In the developed world, the vast majority of adults are wired – at home, at work, and on their smart phones.   Approximately 85% of adults have a high school education, where basic analytics, statistics, mathematics, deductive and inductive reasoning concepts are introduced.  More than 20% going on to earn a bachelors degree.   While a sub-set of these people go on to get specialized training in mathematics, economics, engineering and computer science – the domains that generally lead to what become the “data scientists” in an organization, many more users in an organization can and should be thought of as data scientists.  These people just lack data access and applications to help them take advantage of that data for business advantage.

In the world of software, we tend to think of these people as “business users” – generally the non-technical teams in business lines, managing supply chains, launching products and managing enterprise accounts.   These people are information producers and users, many with both education and on the job training in how to analyze and share business information.  People who understand both data impact and business outcome.  They want access, solutions and real value.  Nobody wants more tools.

When we started Tidemark, we surveyed business owners in multiple roles from finance to sales, to operations, including senior executives to understand the challenge.   Our survey found that the number one issue teams face in both large and mid-size organizations was the lack of analytic applications. We found no ability to do planning and scenario modeling.  The second biggest issue was limited to no web access or remote access.
Business people are asking for smart apps and they are asking for access to these apps everywhere.

As a result, we set out to re-think how business people wanted to work and focused on building smart applications.  With these applications we pre-built an analytic foundation and a completely new computation engine so users could take advantage of packaged applications on a powerful user platform, not be subjected to more tools with no context and limited value.  You can see a quick intro to our approach on smart apps here.

There will always be a need for highly skilled data scientists in organizations of all sizes.  In fact, based on his early work at LinkedIn, and now recognized as a top data scientist, DJ Patil has recently talked about the framework upon which data science and data scientists teams can be built and leveraged throughout an organization, leading to a bigger opportunity: unlock productivity and business value by making everyone a data scientist by giving them easy access to applications that allow them to capture data, do analysis and act from anywhere.

Today everyone is in the data business and the future of work is about everyone having access, control and a voice in helping their organizations compete and win in the marketplace.